21 citations · 56 across the 23 of their papers we have counts for
6 papers · 1 filter
FlowHMR: Physically Plausible Motion Capture from Video
Zhanke Wang, Chengfeng Zhao, Qing Shuai +8
We present FlowHMR, a framework for recovering physically plausible global 3D human motion from monocular video. Previous learning-based methods typically regress human motion dire…
AnimateCanvas: Learning Implicit Motion Planning from Composable Kinematic Cues
Zeyu Ling, Di Kang, Qing Shuai +7
Professional character animation requires both natural motion and precise, versatile control. For example, creators often define the timing of a specified action, control the motio…
GenTrack: Physical Alignment for Robot-Native Motion Generation and Zero-Shot Humanoid Tracking
Zeyu Ling, Xinyao Yu, Renye Yan +4
General-purpose humanoid trackers can execute diverse references, but their zero-shot coverage depends on large embodied corpora that are costly to extend. Text-to-motion generator…
AnyAct: Towards Human Reenactment of Character Motion From Video
Liuhan Chen, Lei Zhong, Jiawei Wang +5
We study the problem of directly deriving an initial human reenactment from a monocular video of a non-human character. Our goal is not to reconstruct the source character itself b…
PRISM: Streaming Human Motion Generation with Per-Joint Latent Decomposition
Zeyu Ling, Qing Shuai, Teng Zhang +3
Text-to-motion generation has advanced with larger corpora and stronger generators, yet many models still rely on holistic frame- or clip-level latents that entangle trajectory, or…
CoMoVi: Co-Generation of 3D Human Motions and Realistic Videos
Chengfeng Zhao, Jiazhi Shu, Yubo Zhao +7
In this paper, we find that the generation of 3D human motions and 2D human videos is intrinsically coupled. 3D motions provide the structural prior for plausibility and consistenc…